Enterprise Data at Huawei: Methods and Practices of Enterprise Data Governance

This book provides an overview of Huawei's data governance and digital transformation journey, covering technology, process, management, and prospects for the future. It offers valuable insights and experiences for readers interested in learning and applying data governance practices.

Format: Paperback / softback
Length: 240 pages
Publication date: 24 November 2022
Publisher: Springer Verlag, Singapore

This comprehensive book provides a systematic exploration of data governance and digital transformation within Huawei, encompassing a wide range of perspectives, including technology, process, management, and more. As a prominent global enterprise operating in over 170 countries and regions, Huawei relies on a robust enterprise data foundation to support its diverse business operations. This foundation is complemented by comprehensive data governance methods, ensuring the effective management and utilization of enterprise data. With a wealth of valuable experience, methodology, standards, solutions, and case studies related to data governance and digital transformation, this book serves as an invaluable resource for readers seeking to gain insights and apply best practices in their own organizations.

The book is structured into four parts and ten chapters, each designed to delve into different aspects of data governance and digital transformation. Drawing upon the concept of "the cognitive world of machines," the book offers insightful perspectives on the future of data governance, including discussions on AI-based governance, data sovereignty, and the establishment of a data ecosystem.

In the first part, the book provides an introduction to data governance and its importance in modern organizations. It explores the challenges faced by organizations in managing and leveraging their data assets, and highlights the role of data governance in ensuring data quality, security, and compliance. The chapter also introduces the key principles and practices of data governance, such as data classification, metadata management, and data lineage tracking.

The second part focuses on the technology aspects of data governance. It discusses the various technologies and tools used in data governance, such as data management platforms, data governance frameworks, and AI-based technologies. The chapter also explores the challenges and opportunities associated with these technologies, such as data integration, data quality management, and data privacy protection.

The third part examines the process aspects of data governance. It discusses the various processes and methodologies used in data governance, such as data governance frameworks, data governance committees, and data governance maturity models. The chapter also highlights the importance of collaboration and communication in data governance, and provides practical tips and strategies for effective data governance implementation.

The fourth part explores the management aspects of data governance. It discusses the roles and responsibilities of data governance stakeholders, such as data owners, data stewards, and data custodians. The chapter also explores the importance of measuring and evaluating the effectiveness of data governance, and provides strategies for continuous improvement and optimization.

Throughout the book, numerous case studies and examples are provided to illustrate the practical application of data governance and digital transformation within Huawei. These case studies showcase Huawei's successful experiences in implementing data governance practices, as well as the challenges and opportunities encountered along the way way.

In conclusion, this comprehensive book provides a valuable resource for professionals and practitioners seeking to understand and implement data governance and digital transformation within their organizations. With its systematic approach, practical insights, and case studies, it offers a comprehensive understanding of the key principles, practices, and technologies involved in data governance and digital transformation. Whether you are a data analyst, data scientist, business leader, or IT professional, this book will help you navigate the complex landscape of data governance and drive your organization's digital transformation journey.

Weight: 409g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811668258
Edition number: 1st ed. 2022